ABSTRACT
Identification and characterization of all proteins expressed by a genome in biological samples represent major challenges in proteomics. Today's commonly used high-throughput approaches combine two-dimensional electrophoresis (2-DE) with peptide mass fingerprinting (PMF) analysis. Although automation is often possible, a number of limitations still adversely affect the rate of protein identification and annotation in 2-DE databases: the sequential excision process of pieces of gel containing protein; the enzymatic digestion step; the interpretation of mass spectra (reliability of identifications); and the manual updating of 2-DE databases. We present a highly automated method that generates a fully annoated 2-DE map. Using a parallel process, all proteins of a 2-DE are first simultaneously digested proteolytically and electro-transferred onto a poly(vinylidene difluoride) membrane. The membrane is then directly scanned by MALDI-TOF MS. After automated protein identification from the obtained peptide mass fingerprints using PeptIdent software (http://www.expasy.ch/tools/peptident.html + ++), a fully annotated 2-D map is created on-line. It is a multidimensional representation of a proteome that contains interpreted PMF data in addition to protein identification results. This "MS-imaging" method represents a major step toward the development of a clinical molecular scanner.
Subject(s)
Image Processing, Computer-Assisted/methods , Peptide Mapping/methods , Automation , Blood Proteins/analysis , Blood Proteins/chemistry , Electrophoresis, Gel, Two-Dimensional/methods , Electrophoresis, Polyacrylamide Gel/methods , Humans , Image Processing, Computer-Assisted/instrumentation , Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization/methods , Trypsin Inhibitor, Kunitz Soybean/analysis , Trypsin Inhibitor, Kunitz Soybean/chemistryABSTRACT
In order to master the overwhelming quantity of data produced by the different laboratories of our Cardiology Division, we are presently developing a centralized database. Our aim is to improve the quality of diagnoses and therapies by constituting patient centered medical files integrating logically the results of the results of the different examinations and allowing for a rapid access to the patient data. The database has to be accessible from an heterogeneous set of PC, MacIntoshes and UNIX workstations. It must have an ergonomic graphic user interface and generate reports which can be sent to the patient physician. It is well known that the requirements for a medical database make its conceptual analysis very difficult. As medical knowledge continually evolves, the examination protocols change and, therefore, the data sets have to be updated. The maintenance of classical databases is usually expensive because it requires specialized staff to alter the database structure and to adapt the user interface. To allow for flexibility, modularity, code reusability and reliability, the object paradigm was applied to a classical relational database. Thanks to the combination of both data structure and behavior in single entities, it is possible to build generic user interfaces which can be easily tailored to the needs of every laboratory of our Cardiology Division.
